Welcome to the AI-Powered Agent Suite! This suite includes several applications designed to leverage AI for various purposes, including stock analysis, health and fitness planning, data visualization, and more. Each application is built using Streamlit for a seamless and interactive user experience.
- Description: An AI-powered tool for analyzing stock market data. It provides real-time stock prices, technical analysis, company fundamentals, and market insights.
- Features:
- Real-time stock prices
- Technical analysis (SMA, RSI, MACD)
- Company fundamentals
- Historical price trends
- Market insights
- Description: A personalized health and fitness planner that generates dietary and fitness plans based on user input.
- Features:
- Personalized dietary plans
- Customized fitness routines
- Goal-oriented recommendations
- Q&A section for plan-related queries
- Description: A data visualization tool that uses AI to provide insights and visualizations from uploaded datasets.
- Features:
- Interactive visualizations
- Deep data insights
- Natural language queries
- SQL query generation
- Statistical analysis
Here are some pictures of the project:
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Clone the Repository:
git clone https://github.com/sanskaryo/DataLens-AI-Agent.git cd DataLens-AI-Agent -
Install Dependencies:
pip install -r requirements.txt
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Set Up Environment Variables:
- Copy
.env.exampleto.envand fill in your API keys. - Example:
GROQ_API_KEY = "your_groq_api_key" TOGETHER_API_KEY = "your_together_api_key" E2B_API_KEY = "your_e2b_api_key"
- Copy
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Stock Analyzer AI Agent:
streamlit run streamlit_finance_app.py
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AI Health & Fitness Planner:
streamlit run fitnessAgent.py
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AI Data Visualization Agent:
streamlit run app.py
- Stock Analyzer: Use the sidebar to access features like quick analysis, technical indicators, and company info. Enter queries in the chat input to get insights.
- Health & Fitness Planner: Fill in your profile details and generate personalized plans. Use the Q&A section for any questions about your plan.
- Data Visualization Agent: Upload a CSV file and use the query input to ask questions about your data. View visualizations and download results.
We welcome contributions to improve our applications! Please follow these steps:
- Fork the repository.
- Create a new branch for your feature or bug fix.
- Commit your changes and push to your fork.
- Submit a pull request with a detailed description of your changes.
This project is licensed under the MIT License. See the LICENSE file for more details.

